Asphalt pavement water film thickness detection and prediction model: A review

Xiao, Ke; Hui, Bing; Qu, Xin; Wang, Hainian; Diab, Aboelkasim; Cao, Min

doi:10.1016/j.jtte.2023.05.001

Cited by 4 publications

(6 citation statements)

References 42 publications

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“…While predictive models for water film depth (WFD)-namely, empirical models, statistical methods, and complex system modeling-offer relatively accurate predictions, those reliant on empirical data or equations show distinct limitations [29][30][31]. These limitations encompass the oversight of factors such as pavement texture and permeability, restricted applicability linked to localized empirical data, the inadequacy of fixed rainfall intensity values in capturing diverse precipitation environments, and constraints in accounting for various road surface types in WFD computations [26,[32][33][34].…”

Section: Source Equation Formmentioning

confidence: 99%

“…Key parameters include the length of surface drainage (L), rainfall intensity (I), pavement slope (i or the angle α between the pavement and the horizontal line, i = sinα ≈ tanα), initial depth of the water film (h 0 ), initial velocity of raindrops (u 0 ), and rainfall angle (β). Domestic and international scholars have explored methods such as multiple linear regression and range analysis to assess the significance of each parameter in influencing pavement water film depth under rainfall conditions [6,29]. Significance tests have been employed to rank the degree of influence of each factor on water film depth.…”

Section: Intervening Factors On Pavement Wfdmentioning

confidence: 99%

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A New Water Film Depth Prediction Model for Pavement Surface Drainage

Zhao,

Zhou,

Zhao

et al. 2024

Infrastructures

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The prediction of the water film depth (WFD) on the road surface can help with road skid resistance research and reduce the risk associated with driving on rainy days. At present, there are many empirical and analytical models based on drainage length, slope, rainfall intensity and other parameters. Considering the influence of road surface runoff and starting from the Reynolds number formula of road surface water flow, a new road surface WFD calculation formula that considers the movement state of laminar water flow is derived. The results show that the changing trends of various parameters in the prediction model (drainage length, rainfall intensity, road slope) affecting WFD are consistent with those of the existing model. It is also found that the initial water film depth, initial speed of rainwater, and rainfall angle have little impact on WFD. The predicted value of the model has a suitable matching degree compared with the classical empirical model, which provides a new approach to the prediction of road water film depth.

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Section: Source Equation Formmentioning

confidence: 99%

Section: Intervening Factors On Pavement Wfdmentioning

confidence: 99%

A New Water Film Depth Prediction Model for Pavement Surface Drainage

Zhao,

Zhou,

Zhao

et al. 2024

Infrastructures

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“…There is no standardized definition of a water depth. Nevertheless, researchers commonly refer to the following notions [10,11] (Figure 1): the "above asperity" depth (Figure 1a), which expresses the thickness of the water film above the asperities of the road surface, and the "mean" depth (Figure 1b), which corresponds to an average depth obtained by dividing a total volume of water by the surface wetted by this volume. In this paper, the second definition will be used.…”

Section: Background 21 Measurement and Estimation Of Water Depthmentioning

confidence: 99%

“…In this the second definition will be used. Among recent reviews dedicated to technologies that can be applied to road runways [10][11][12], it has been found that infrared spectroscopy methods are the mo cient compared to other contactless technologies. Despite their many advantages accuracy, reliable recognition of various contaminants, etc.…”

Section: Measurement and Estimation Of Water Depthmentioning

confidence: 99%

“…Recently, Riahi and coauthors [9] dev a similar system and, using a trailer equipped with a passenger car's tire, found pro relationships between the acceleration amplitude (root mean square of an accele time signal) and the water depth. Among recent reviews dedicated to technologies that can be applied to roads and runways [10][11][12], it has been found that infrared spectroscopy methods are the most efficient compared to other contactless technologies. Despite their many advantages (high accuracy, reliable recognition of various contaminants, etc.…”

Section: Measurement and Estimation Of Water Depthmentioning

confidence: 99%

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Estimation of Road Wetness from a Passenger Car

Edjeou,

Riahi,

Gennesseaux

et al. 2023

Lubricants

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This paper presents an evaluation of a system aiming at estimating water depths on a road surface. Using accelerometers, the system records the vibrations of a wheel arch liner due to impacts of water droplets. The system setup, including the location of the accelerometers on a wheel arch and the data acquisition, is described. Tests were performed with a passenger car on various road surfaces and at different vehicle speeds and water depths. Signals recorded by the accelerometers are filtered and processed. The link between the acceleration amplitude, the water depth, and the vehicle speed is consistent with results from previous studies. The effect of the surface texture is less obvious and needs further investigations. A mathematical model has been developed to relate the acceleration amplitude to the water depth. The potential application of the developed system to on-board evaluation of pavement wetness, and consequently the pavement skid resistance, is discussed. Perspectives for driver assistance, or more generally, for autonomous driving to improve traffic safety, are also highlighted.

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Simulation of Water Flow Path Length (WFPL) and Water Film Depth (WFD) for Wide Expressway Asphalt Pavement

Cheng,

Liang,

et al. 2024

Buildings

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This paper simulates actual rainfall conditions and raindrops flowing to form a water flow path (WFP) on the pavement surface of the wide expressway. Then, the different linear combination conditions, including longitudinal slope (LS), transverse slope (superelevation, TS), gradual change rate of TS, and pavement width (PW), were simulated and analyzed. The results show that (1) the influence of each linear index on the maximum water film path length (WFPLmax) and maximum water flow depth (WFDmax) differs (according to the absolute values of Beta, LS has the greatest influence on WFPLmax, and PW has the greatest influence on the WFDmax for both straight-line and circular-curve sections); (2) when the design value of LS is between 1.1% and 4%, the WFDmax can be effectively reduced by lowering the value of LS; (3) in the case of a high design value of LS, it can be considered to increase the TS of the pavement arch from 2% to 2.5% to effectively reduce the WFPLmax, and the wider PW, the better the reducing effect; (4) while widening the expressway, adjusting the TS from 2% to 2.5% can effectively offset the increasing effect of PW on the WFDmax. This research aims to fill the research gap in the simulation of runoff characteristics of wide expressway asphalt pavements and to improve the alignment design of expressways from the drainage perspective for the improvement of driving safety.

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Asphalt pavement water film thickness detection and prediction model: A review

Cited by 4 publications

References 42 publications

A New Water Film Depth Prediction Model for Pavement Surface Drainage

A New Water Film Depth Prediction Model for Pavement Surface Drainage

Estimation of Road Wetness from a Passenger Car

Simulation of Water Flow Path Length (WFPL) and Water Film Depth (WFD) for Wide Expressway Asphalt Pavement

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